With our single-agent experiences under our belt, we can move on to the more complex but equally entertaining world of working in multi-agent environments, training multiple agents to work in the same environment in a co-operative or competitive fashion. This also opens up several new opportunities for training agents with adversarial self-play, cooperative self-play, competitive self-play, and more. The possibilities become endless here, and this may be the true holy grail of AI.
In this chapter, we are going to cover several aspects of multi-agent training environments and the main section topics are highlighted here:
- Adversarial and cooperative self-play
- Competitive self-play
- Multi-brain play
- Adding individuality with intrinsic rewards
- Extrinsic rewards for individuality
This chapter assumes you have covered the three previous chapters and...
